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Purpose Methods Results Conclusion To evaluate the feasibility and acceptability of self‐tonometry by glaucoma patients using iCare® Home2 (ICH2) and a smartphone application, without healthcare personnel supervision.After downloading a smartphone application, participants learned to handle the ICH2 via an instruction film, measured their intraocular pressure (IOP) and transferred the data to the caregiver via the application. Participants' measurements were compared to healthcare personnel measurements using Goldmann applanation tonometry (GAT). Participants answered questionnaires about their experience of self‐tonometry.Twenty‐eight participants were included in the study and three of them dropped off. There was no statistically significant difference between the last measurements obtained with ICH2 by the participants and the GAT measurements for the right and the left eye, p = 0.781 and p = 0.888 respectively. The inter‐user agreement was good to excellent between the last measurements obtained with ICH2 by the participants and the GAT measurements for the right and the left eye (ICC 0.907 and 0.830 respectively). The overall impression of the participants was very positive, with 92% happy (a lot or completely) with the instruction film and 88% happy (a lot or completely) with the smartphone application. Thirty‐six percent would have preferred to have an instructor by their side.Our study showed the feasibility and acceptability of self‐tonometry with iCare® Home2 and a smartphone application without the supervision of a healthcare provider in a group of motivated glaucoma patients. [ABSTRACT FROM AUTHOR]

Background: Digital innovations can reduce the global burden of depression by facilitating timely and scalable interventions. In recent years, the number of commercial Digital Health Interventions for Depression (DHIDs) has been on the rise. However, there is limited knowledge on their content and underpinning scientific evidence. This study aimed to: (i) identify the top-funded companies offering DHIDs and (ii) provide an overview of their interventions, including scientific evidence, psychotherapeutic approaches and use of novel technologies. Methods: A systematic search was conducted using two venture capital databases to identify the top-30 funded companies offering DHIDs. In addition, studies related to the DHIDs' were identified via academic databases and hand-searching. The methodological quality of the publications was evaluated using the Mixed Methods Appraisal Tool. Results: The top-30 funded companies offering DHIDs received a total funding of 2,592 million USD. Less than half of the companies produced any scientific research associated with their DHIDs, with a total of 83 publications identified. Twenty-five publications were randomised control trials, of which 15 reported moderate-to-large effects in reducing depression symptoms. Regarding novel technologies, few DHIDs incorporated the use of conversational agents or low-burden sensing technologies. Conclusions: Funding received by top-funded companies was not related to the amount of scientific evidence provided on their DHIDs. There was a strong variation in the quantity of evidence produced and an overall need for more rigorous effectiveness trials. Few DHIDs used automated approaches such as conversational agents, limiting their scalability. [ABSTRACT FROM AUTHOR]

Mobile applications in crop protection especially for speedy pest diagnosis, monitoring, and management are increasingly gaining global attention and support. An understanding of the awareness and perception of the youths, particularly students in tertiary institutions (who are heavy users of smartphones), on the use of smartphone applications for crop protection, is crucial for sharpening their orientations towards embracing the digital ecosystem in agriculture. The imperativeness is evident in the ongoing government drive towards promoting students' engagement in digital agriculture as accommodated in the National Agricultural Technology and Innovation Policy (2022–2027). Consequently, this study investigated awareness and perception of mobile phone applications among crop and agricultural extension-related final-year students in selected Universities in Southwest Nigeria. A multistage sampling procedure was used in selecting 407 students. Data were obtained with the aid of questionnaires. Data were summarized using descriptive statistics such as frequency counts, percentages, mean and standard deviation using SPSS software. Findings show that very few (less than 8%) of the respondents were aware of the usage of specific smart/android phone applications for pest identification, disease diagnosis, and weather forecasting. Less than 4% ever used smart/android phones for pest identification, crop protection, and information sourcing on disease diagnosis and management. However, their perception of the need for pest and disease diagnosis as a foundation step to enhance crop protection (4.65 points on a scale of 5), and readiness to use android/smartphone applications for this purpose (MS = 4.45) was positive. There are enormous implications for increased awareness and knowledge sharing on the use of android/smartphone applications for crop protection and other interventions to promote digital agriculture among students in Nigeria. [ABSTRACT FROM AUTHOR]

Young adults are a high-risk population for developing smartphone addiction (SA), which bring about social issues. One theoretically and empirically supported proximal risk factor of SA is preference for smartphone-based internet applications (PSIA). However, most previous studies ignore gender difference and symptomatic heterogeneity of SA. Besides, many previous data analyses contain non-addicts, and the results derived might not be applicable to smartphone addicts. To bridging the gap, we used a symptom-level network analysis to assess gender differences in the links between preferences for 8 smartphone-based internet applications and 4 SA symptoms among young adults with high-level phone addiction (619 women and 415 men). The results showed that: (1) The relationship between the preference for video and the "loss of control" symptom was more pronounced in female addicts compared to their male counterparts. (2) Shopping app had stronger bridge centrality in women's smartphone applications-SA network, which was positively linked with more SA symptoms. (3) Our research identified marginal gender differences in smartphone addicts' psychological networks, with female addicts showing stronger links between social media/eBook preferences and withdrawal symptoms, and male addicts displaying a stronger connection between gaming/eBook and other smartphone activities. The study provides a visualized network association and network metrics for understanding the relationship between PSIA and SA. We propose adopting a selective processing hypothesis and an evolutionary psychology perspective to aid in understanding these gender differences. [ABSTRACT FROM AUTHOR]

Copyright of Egyptian Journal of Information Sciences is the property of Beni Suef University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In recent years, increasing attention has been paid to identifying new approaches to improve workplace well-being and manage stress with the help of m-health solutions. The primary purpose of this review is to provide an overview of the current use of smartphone applications integrated with wearable technologies in stress management and the promotion of well-being in the workplace. A key terms literature search was performed using multiple electronic databases. The review process followed the international PRISMA statement guidelines. A quality assessment was conducted using the Mixed Methods Appraisal Tool. A total of 25 eligible papers published between 2016 and 2023 were included. Interventions proposed were heterogeneous and primarily based on smartphone applications (72%). 84% of the interventions had background theories, with a high preference for Mindfulness. Interventions were reported as generally significant, and the combined use of smartphone applications and wearable technologies increased awareness at the individual and collective levels. In conclusion, the review demonstrates how the interventions developed through the synergy of technologies can effectively promote well-being and reduce stress in the workplace context, decreasing the stigma still related to mental health and increasing peer support strategies. This work opens the doors to several possibilities for future research. It could be interesting to indagate more in-depth the value of integration between technologies and, eventually, the integration with more traditional type of interventions, e.g., face-to-face activities, evaluating if this synergy can amplify and strengthen the results. Protocol registration: The review protocol was registered with PROSPERO: CRD42023423126 (May 2nd, 2023). [ABSTRACT FROM AUTHOR]

The rapid uprising technologies of smartphone applications and software introduced a new era for analytical detection techniques. It has transformed bench-top laboratory methods into simpler ones depending on cost-effective, portable, and widely accessible devices. In this work, two high performance thin layer chromatographic (HPTLC) methods were developed based on smartphone's camera detection and either ImageJ desktop software or Color-Picker smartphone's application as alternative techniques to conventional densitometric detection. A mixture of Naltrexone hydrochloride (NAL) and Bupropion hydrochloride (BUP) was chromatographed on HPTLC- plates using ethyl acetate, methanol, acetone, and glacial acetic acid (3:6:1:0.5, by volume) as a developing system. The developed plates were scanned at 203 nm for the densitometric analysis, then visualized by modified Dragendorff's reagent and shot by a smartphone's camera. The captured images were uploaded to either ImageJ software or Color-Picker application to detect the separated spots. The results derived from the three detection methods were compared over the concentration range of 0.4–24 & 0.6–18 µg/band for the densitometric method, 0.4–24 & 2–24 µg/band for ImageJ built method and 0.8–20 & 5–20 µg/band for Color Picker built method for NAL and BUP, respectively. The methods were found to be appropriate for assaying both active drug substances in pure forms and combined in marketed pharmaceutical formulations. The excellent sustainability of densitometric and ImageJ-based methods enabled also the assessment of their dosage form content uniformity. The greenness and sustainability of the methods were assessed by three metric tools, namely Green Analytical Procedure Index (GAPI), Analytical GREEnness Metric Approach (AGREE), and White Analytical Chemistry (WAC). The assessments results confirmed the sustainability and superiority of the proposed methods in terms of sample treatment, waste mount, energy consumption, cost, and number of analyzed samples per an hour. [ABSTRACT FROM AUTHOR]

This work presents a 12-element multiple-input–multiple-output (MIMO) wideband antenna array for mobile smartphones. The antenna element is mainly composed of two parts, greatly improving the antenna array bandwidth: one is a meandering, looped radiating element and the other is a U-shaped slot. For the antenna element design, the meandering, looped radiating element measures 12.95 × 6 mm2, while the U-shaped slot has a size of 15 × 3 mm2. Meanwhile, the reflection coefficient indicates that the designed antenna array operates at 3.3 GHz with a bandwidth of 500 MHz; the transmission coefficient shows that the isolation between the antenna elements is better than 12 dB. In addition, more antenna array performances are presented, including nearly omnidirectional radiation characteristics, antenna efficiency ranging from approximately 17 to 60%, envelope correlation coefficients (ECCs) below 0.065, and diversity gain (DG) values of the MIMO antenna system close to 10 dB. The measurement results are highly consistent with the simulation results of the designed wideband antenna array, indicating its great potential for future practical engineering applications. [ABSTRACT FROM AUTHOR]

Abstract Background Digital innovations can reduce the global burden of depression by facilitating timely and scalable interventions. In recent years, the number of commercial Digital Health Interventions for Depression (DHIDs) has been on the rise. However, there is limited knowledge on their content and underpinning scientific evidence. This study aimed to: (i) identify the top-funded companies offering DHIDs and (ii) provide an overview of their interventions, including scientific evidence, psychotherapeutic approaches and use of novel technologies. Methods A systematic search was conducted using two venture capital databases to identify the top-30 funded companies offering DHIDs. In addition, studies related to the DHIDs’ were identified via academic databases and hand-searching. The methodological quality of the publications was evaluated using the Mixed Methods Appraisal Tool. Results The top-30 funded companies offering DHIDs received a total funding of 2,592 million USD. Less than half of the companies produced any scientific research associated with their DHIDs, with a total of 83 publications identified. Twenty-five publications were randomised control trials, of which 15 reported moderate-to-large effects in reducing depression symptoms. Regarding novel technologies, few DHIDs incorporated the use of conversational agents or low-burden sensing technologies. Conclusions Funding received by top-funded companies was not related to the amount of scientific evidence provided on their DHIDs. There was a strong variation in the quantity of evidence produced and an overall need for more rigorous effectiveness trials. Few DHIDs used automated approaches such as conversational agents, limiting their scalability.

Abstract Mobile applications in crop protection especially for speedy pest diagnosis, monitoring, and management are increasingly gaining global attention and support. An understanding of the awareness and perception of the youths, particularly students in tertiary institutions (who are heavy users of smartphones), on the use of smartphone applications for crop protection, is crucial for sharpening their orientations towards embracing the digital ecosystem in agriculture. The imperativeness is evident in the ongoing government drive towards promoting students’ engagement in digital agriculture as accommodated in the National Agricultural Technology and Innovation Policy (2022–2027). Consequently, this study investigated awareness and perception of mobile phone applications among crop and agricultural extension-related final-year students in selected Universities in Southwest Nigeria. A multistage sampling procedure was used in selecting 407 students. Data were obtained with the aid of questionnaires. Data were summarized using descriptive statistics such as frequency counts, percentages, mean and standard deviation using SPSS software. Findings show that very few (less than 8%) of the respondents were aware of the usage of specific smart/android phone applications for pest identification, disease diagnosis, and weather forecasting. Less than 4% ever used smart/android phones for pest identification, crop protection, and information sourcing on disease diagnosis and management. However, their perception of the need for pest and disease diagnosis as a foundation step to enhance crop protection (4.65 points on a scale of 5), and readiness to use android/smartphone applications for this purpose (MS = 4.45) was positive. There are enormous implications for increased awareness and knowledge sharing on the use of android/smartphone applications for crop protection and other interventions to promote digital agriculture among students in Nigeria.

Abstract The rapid uprising technologies of smartphone applications and software introduced a new era for analytical detection techniques. It has transformed bench-top laboratory methods into simpler ones depending on cost-effective, portable, and widely accessible devices. In this work, two high performance thin layer chromatographic (HPTLC) methods were developed based on smartphone’s camera detection and either ImageJ desktop software or Color-Picker smartphone’s application as alternative techniques to conventional densitometric detection. A mixture of Naltrexone hydrochloride (NAL) and Bupropion hydrochloride (BUP) was chromatographed on HPTLC- plates using ethyl acetate, methanol, acetone, and glacial acetic acid (3:6:1:0.5, by volume) as a developing system. The developed plates were scanned at 203 nm for the densitometric analysis, then visualized by modified Dragendorff’s reagent and shot by a smartphone’s camera. The captured images were uploaded to either ImageJ software or Color-Picker application to detect the separated spots. The results derived from the three detection methods were compared over the concentration range of 0.4–24 & 0.6–18 µg/band for the densitometric method, 0.4–24 & 2–24 µg/band for ImageJ built method and 0.8–20 & 5–20 µg/band for Color Picker built method for NAL and BUP, respectively. The methods were found to be appropriate for assaying both active drug substances in pure forms and combined in marketed pharmaceutical formulations. The excellent sustainability of densitometric and ImageJ-based methods enabled also the assessment of their dosage form content uniformity. The greenness and sustainability of the methods were assessed by three metric tools, namely Green Analytical Procedure Index (GAPI), Analytical GREEnness Metric Approach (AGREE), and White Analytical Chemistry (WAC). The assessments results confirmed the sustainability and superiority of the proposed methods in terms of sample treatment, waste mount, energy consumption, cost, and number of analyzed samples per an hour.

Background: Smartphones play a crucial role in our everyday life. Smartphones help users to develop social connections with others, gain information and entertain themselves through various applications. With the widespread use of smartphone, the number of smartphone users has been increasing worldwide. As smartphones are getting popular, smartphone addiction has become a serious mental health problem among adolescents. Objectives: To find out significant differences in smartphone addiction among adolescents with respect to their gender and locale. Methodology: Descriptive survey method was used for conducting the study. The sample consists of 200 adolescents of government and private schools from Jammu and Kathua. 'Smartphone Addiction Scale' (2021) developed by Vijayshri and Masaud Ansari was used for data collection. Results: It was found that smartphone addiction was significantly higher among female adolescents (M=65.34) as compared to their male counterparts (58.61). Further, it was also found that smartphone addiction was significantly higher in urban adolescents (M=64.37) than rural adolescents (M=59.08). Conclusion: In order to combat smartphone addiction among adolescents, we advise the creation of healthy environment at the family and school levels. Teachers should provide knowledge to the students about smartphone security tips and educational programmes should be organized for protecting psychological well-being of the adolescents. [ABSTRACT FROM AUTHOR]

This study explored Kurdish EFL learners' attitudes toward using smartphone applications for language learning. The data collection instrument was a five-point Likert-Scale questionnaire and the population was (101) students from departments of Medical Laboratory Science, General Science, and Chemistry Science - Charmo University. The results showed that the learners generally have a positive attitude towards using smartphone applications for English language learning. Also, the results suggest that learners generally agree that smartphone applications are useful and accessible tool for language learning. Regarding social media applications, the results indicated that learners who use social media platforms generally look for language-learning content. Nonetheless, the findings demonstrated that higher utilization of smartphone applications may not be necessarily associated with a perceived gain in proficiency. Consequently, language teachers must lead and assist students in learning how to utilize applications in general and those specifically created for language learning in particular. Therefore, EFL teachers' roles change from manager to facilitator. It is the teacher's responsibility to assist students in locating suitable material on the internet, which leads to mastery of the target language. [ABSTRACT FROM AUTHOR]

Yi-Hsien Shiao,1,2 Chung-Chieh Yu,3 Yuan-Chieh Yeh1,4 1Department of Traditional Chinese Medicine, Chang Gung Memorial Hospital, Keelung Medical Center, Keelung, Taiwan; 2Graduate Institute of Natural Products, College of Medicine, Chang Gung University, Taoyuan, Taiwan; 3Department of Chest, Critical Care, and Sleep Medicine, Chang Gung Memorial Hospital, Keelung Medical Center, Keelung, Taiwan; 4Program in Molecular Medicine, College of Life Sciences, National Yang Ming Chiao Tung University, Taipei, TaiwanCorrespondence: Yuan-Chieh Yeh, Department of Traditional Chinese Medicine, Chang Gung Memorial Hospital, Keelung Medical Center, No. 222, Maijin Road, Anle Dist, Keelung, 204, Taiwan, Tel +886 02-24313131 ext 2777, Fax +886 02-24313161, Email b9005030@gmail.comPurpose: Obstructive sleep apnea (OSA) is a common breathing disorder during sleep that is associated with symptoms such as snoring, excessive daytime sleepiness, and breathing interruptions. Polysomnography (PSG) is the most reliable diagnostic test for OSA; however, its high cost and lengthy testing duration make it difficult to access for many patients. With the availability of free snore applications for home-monitoring, this study aimed to validate the top three ranked snore applications, namely SnoreLab (SL), Anti Snore Solution (ASS), and Sleep Cycle Alarm (SCA), using PSG.Patients and Methods: Sixty participants underwent an overnight PSG while simultaneously using three identical smartphones with the tested apps to gather sleep and snoring data.Results: The study discovered that all three applications were significantly correlated with the total recording time and snore counts of PSG, with ASS showing good agreement with snore counts. Furthermore, the Snore Score, Time Snoring of SL, and Sleep Quality of SCA had a significant correlation with the natural logarithm of apnea hypopnea index (lnAHI) of PSG. The Snore Score of SL and the Sleep Quality of SCA were shown to be useful for evaluating snore severity and for pre-diagnosing or predicting OSA above moderate levels.Conclusion: These findings suggest that some parameters of free snore applications can be employed to monitor OSA progress, and future research could involve adjusted algorithms and larger-scale studies to further authenticate these downloadable snore and sleep applications.Keywords: polysomnography, snoring, smartphone applications, apps, obstructive sleep apnea, apnea hypopnea index

Abstract Background Physical activity (PA) interventions have an encouraging role in gestational diabetes mellitus (GDM) management. Digital technologies can potentially be used at scale to support PA. The aim of this study was to assess the feasibility and acceptability of + Stay-Active: a complex intervention which combines motivational interviewing with a smartphone application to promote PA levels in women with GDM. Methods This non-randomised feasibility study used a mixed methods approach. Participants were recruited from the GDM antenatal clinic at Oxford University Hospitals. Following baseline assessments (visit 1) including self-reported and device determined PA measurements (wrist worn accelerometer), women participated in an online motivational interview, and then downloaded (visit 2) and used the Stay-Active app (Android or iOS). Women had access to Stay-Active until 36 weeks’ gestation, when acceptability and PA levels were reassessed (visit 3). The primary outcome measures were recruitment and retention rates, participant engagement, and acceptability and fidelity of the intervention. Secondary outcome measures included PA levels, app usage, blood glucose and perinatal outcomes. Descriptive statistics were performed for assessments at study visits. Statistics software package Stata 14 and R were used. Results Over the recruitment period (46 weeks), 114 of 285 women met inclusion criteria and 67 (58%) enrolled in the study. Mean recruitment rate of 1.5 participants/clinic with 2.5 women/clinic meeting inclusion criteria. Fifty-six (83%) received the intervention at visit 2 and 53 (79%) completed the study. Compliance to accelerometer measurement protocols were sufficient in 78% of participants (52/67); wearing the device for more than 10 h on 5 or more days at baseline and 61% (41/67) at 36 weeks. There was high engagement with Stay-Active; 82% (55/67) of participants set goals on Stay-Active. Sustained engagement was evident, participants regularly accessed and logged multiples activities on Stay-Active. The intervention was deemed acceptable; 85% of women rated their care was satisfactory or above, supported by written feedback. Conclusions This combined intervention was feasible and accepted. Recruitment rates were lower than expected. However, retention rates remained satisfactory and participant compliance with PA measurements and engagement was a high. Future work will explore the intervention’s efficacy to increase PA and impact on clinical outcomes. Trial registration The study has received a favourable opinion from South Central—Hampshire B Research Ethics Committee; REC reference: 20/SC/0342. ISRCTN11366562.

Introduction: To describe the self-care challenges, diabetes technology awareness, current use, and satisfaction among adults with type 1 diabetes and parents of children with type 1 diabetes in Singapore. Methods: An anonymous online survey was administered between November 2020 and October 2021. Data are presented as mean (standard deviation) or count (percentages). Comparisons between groups were done using the independent samples T-test. Results: 251 people (176 adults, 75 parents) participated. The most challenging self-care burdens were carbohydrate counting (24.4%) among adults and insulin dose calculations (28%) among parents. Nocturnal awakenings for diabetes care of their child were a common event (25.3%). Despite high awareness about continuous glucose monitoring devices (77.8% adults, 78.7% parents) the use (24.9% adults, 55% children) remained low. Both adults and parents of children with type 1 diabetes found continuous glucose monitoring to be liberating and less restrictive. Despite overall low insulin pump use (23.9% adults, 29.3% children); satisfaction scores were higher among insulin pump users than insulin pen users (P = 0.02). Conclusion: Carbohydrate counting and insulin dose calculations were the most challenging self-care tasks among people with type 1 diabetes in Singapore. Diabetes technology use was relatively low in Singapore. Continuous glucose monitoring and Insulin pump users found them to be beneficial.

Accidental exposure to potentially poisonous plants is a common reason for contacting poisons information centres. Although most exposures are mild, early identification can be critical for severe cases. Smartphone apps that use image recognition can serve as an alternative to traditional botanist identification. This study investigates the accuracy of smartphone applications compared to botanist identification in real-life plant exposure cases referred to the Queensland Poisons Information Centre. This prospective observational study analysed data from 25 plant exposure cases between February 2022 and January 2023. In these cases, images were referred to a botanist for identification and reviewed by six researchers using six different plant identification applications (Google Lens™, PictureThis, PlantSnap, LeafSnap, Plant Identifier, and Pl@ntnet™). The researchers’ identifications were then compared to the botanist’s identification. The accuracy of the applications varied considerably, PictureThis was the best, with 74% correct identification per exposure, followed by Plant Identifier and Pl@ntnet™ (both 72%). PlantSnap had the lowest accuracy (38%). Agreement between researchers using the same application also showed variation. Current smartphone plant identification applications are not reliable enough for poison information centres to use in guiding advice for plant exposure calls. Botanist identification remains the gold standard. Clinicians should be wary of their use in real-world scenarios.

Background: Physical activity (PA) interventions have an encouraging role in gestational diabetes mellitus (GDM) management. Digital technologies can potentially be used at scale to support PA. The aim of this study was to assess the feasibility and acceptability of + Stay-Active: a complex intervention which combines motivational interviewing with a smartphone application to promote PA levels in women with GDM. Methods: This non-randomised feasibility study used a mixed methods approach. Participants were recruited from the GDM antenatal clinic at Oxford University Hospitals. Following baseline assessments (visit 1) including self-reported and device determined PA measurements (wrist worn accelerometer), women participated in an online motivational interview, and then downloaded (visit 2) and used the Stay-Active app (Android or iOS). Women had access to Stay-Active until 36 weeks' gestation, when acceptability and PA levels were reassessed (visit 3). The primary outcome measures were recruitment and retention rates, participant engagement, and acceptability and fidelity of the intervention. Secondary outcome measures included PA levels, app usage, blood glucose and perinatal outcomes. Descriptive statistics were performed for assessments at study visits. Statistics software package Stata 14 and R were used. Results: Over the recruitment period (46 weeks), 114 of 285 women met inclusion criteria and 67 (58%) enrolled in the study. Mean recruitment rate of 1.5 participants/clinic with 2.5 women/clinic meeting inclusion criteria. Fifty-six (83%) received the intervention at visit 2 and 53 (79%) completed the study. Compliance to accelerometer measurement protocols were sufficient in 78% of participants (52/67); wearing the device for more than 10 h on 5 or more days at baseline and 61% (41/67) at 36 weeks. There was high engagement with Stay-Active; 82% (55/67) of participants set goals on Stay-Active. Sustained engagement was evident, participants regularly accessed and logged multiples activities on Stay-Active. The intervention was deemed acceptable; 85% of women rated their care was satisfactory or above, supported by written feedback. Conclusions: This combined intervention was feasible and accepted. Recruitment rates were lower than expected. However, retention rates remained satisfactory and participant compliance with PA measurements and engagement was a high. Future work will explore the intervention's efficacy to increase PA and impact on clinical outcomes. Trial registration: The study has received a favourable opinion from South Central—Hampshire B Research Ethics Committee; REC reference: 20/SC/0342. ISRCTN11366562. [ABSTRACT FROM AUTHOR]

Background and aims: iCanQuit is a smartphone application (app) proven efficacious for smoking cessation in a Phase III randomized controlled trial (RCT). This study aimed to measure whether medications approved by the US Food and Drug Administration (FDA) for smoking cessation would further enhance the efficacy of iCanQuit, relative to its parent trial comparator—the National Cancer Institute's (NCI's) QuitGuide app. Design: Secondary analysis of the entire parent trial sample of a two‐group (iCanQuit and QuitGuide), stratified, doubled‐blind RCT. Setting: United States. Participants: Participants who reported using an FDA‐approved cessation medication on their own (n = 619) and those who reported no use of cessation medications (n = 1469). Interventions: Participants were randomized to receive iCanQuit app or NCI's QuitGuide app. Measurements Use of FDA‐approved medications was measured at 3 months post‐randomization. Smoking cessation outcomes were measured at 3, 6 and 12 months. The primary outcome was 12‐month self‐reported 30‐day point prevalence abstinence (PPA). Findings The data retention rate at the 12‐month follow‐up was 94.0%. Participants were aged 38.5 years, 71.0% female, 36.6% minority race/ethnicity, 40.6% high school or less education, residing in all 50 US States and smoking 19.2 cigarettes/day. The 29.6% of all participants who used medications were more likely to choose nicotine replacement therapy (NRT; 78.8%) than other cessation medications (i.e. varenicline or bupropion; 18.3 and 10.5%, respectively) and use did not differ by app treatment assignment (all P > 0.05). There was a significant (P = 0.049) interaction between medication use and app treatment assignment on PPA. Specifically, 12‐month quit rates were 34% for iCanQuit versus 20% for QuitGuide [odds ratio (OR) = 2.36, 95% confidence interval (CI) = 1.59, 3.49] among participants reporting any medication use, whereas among participants reporting no medication use, quit rates were 28% for iCanQuit versus 22% for QuitGuide (OR = 1.41, 95% CI = 1.09, 1.82). Results were stronger for those using only NRT: 40% quit rates for iCanQuit versus 18% quit rates for QuitGuide (OR = 3.57, 95% CI = 2.20, 5.79). Conclusions: The iCanQuit smartphone app for smoking cessation was more efficacious than the QuitGuide smartphone app, regardless of whether participants used medications to aid cessation. Smoking cessation medications, especially nicotine replacement therapy, might enhance the efficacy of the iCanQuit app. [ABSTRACT FROM AUTHOR]

Copyright of Movement & Sport Sciences / Science & Motricité is the property of EDP Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The purposes were to examine the criterion-related validity of the steps estimated by consumer-wearable activity trackers (wristworn activity trackers: Fitbit Ace 2, Garmin Vivofit Jr, and Xiomi Mi Band 5; smartphone applications: Pedometer, Pedometer Pacer Health, and Google Fit/Apple Health) and their comparability in primary schoolchildren under controlled conditions. An initial sample of 66 primary schoolchildren (final sample = 56; 46.4% females), aged 9-12 years old (mean = 10.4 ± 1.0 years), wore three wrist-worn activity trackers (Fitbit Ace 2, Garmin Vivofit Jr 2, and Xiaomi Mi Band 5) on their non-dominant wrist and had three applications in two smartphones (Pedometer, Pedometer Pacer Health, and Google Fit/Apple Health for Android/iOS installed in Samsung Galaxy S20+/iPhone 11 Pro Max) in simulated front trouser pockets. Primary schoolchildren's steps estimated by the consumer-wearable activity trackers and the video-based counting independently by two researchers (gold standard) were recorded while they performed a 200-meter course in slow, normal and brisk pace walking, and running conditions. Results showed that the criterion-related validity of the step scores estimated by the three Samsung applications and the Garmin Vivofit Jr 2 were good-excellent in the four walking/running conditions (e.g., MAPE = 0.6 - 2.3%; lower 95% CI of the ICC = 0.81 - 0.99), as well as being comparable. However, the Apple applications, Fitbit Ace 2, and Xiaomi Mi Band 5 showed poor criterion-related validity and comparability on some walking/running conditions (e.g., lower 95% CI of the ICC < 0.70). Although, as in real life primary schoolchildren also place their smartphones in other parts (e.g., schoolbags, hands or even somewhere away from the body), the criterion-related validity of the Garmin Vivofit Jr 2 potentially would be considerably higher than that of the Samsung applications. The findings of the present study highlight the potential of the Garmin Vivofit Jr 2 for monitoring primary schoolchildren's steps under controlled conditions. [ABSTRACT FROM AUTHOR]

Introduction: To describe the self-care challenges, diabetes technology awareness, current use, and satisfaction among adults with type 1 diabetes and parents of children with type 1 diabetes in Singapore. Methods: An anonymous online survey was administered between November 2020 and October 2021. Data are presented as mean (standard deviation) or count (percentages). Comparisons between groups were done using the independent samples T-test. Results: 251 people (176 adults, 75 parents) participated. The most challenging self-care burdens were carbohydrate counting (24.4%) among adults and insulin dose calculations (28%) among parents. Nocturnal awakenings for diabetes care of their child were a common event (25.3%). Despite high awareness about continuous glucose monitoring devices (77.8% adults, 78.7% parents) the use (24.9% adults, 55% children) remained low. Both adults and parents of children with type 1 diabetes found continuous glucose monitoring to be liberating and less restrictive. Despite overall low insulin pump use (23.9% adults, 29.3% children); satisfaction scores were higher among insulin pump users than insulin pen users (P = 0.02). Conclusion: Carbohydrate counting and insulin dose calculations were the most challenging self-care tasks among people with type 1 diabetes in Singapore. Diabetes technology use was relatively low in Singapore. Continuous glucose monitoring and Insulin pump users found them to be beneficial. [ABSTRACT FROM AUTHOR]

In response to the increasing demands for 4G LTE and 5G smartphone applications, this study presents a compact and integrated prototype designed to cover sub-6 GHz and 5G mm-wave bands with high-frequency ratios. The proposed integrated design incorporates two multiple-input-multiple-output (MIMO) configurations: a $2\times2$ dual-band planar inverted-F antenna (PIFA) MIMO for sub-6 GHz and an array of eight elements for mm-wave. Proximity placement (2.5 mm separation) of mm-wave elements on smartphone RIM achieves compact array size with optimal beamforming, coverage, and interference prevention. Utilizing a meandered patch and truncated ground, the proposed PIFA achieves a size of 37 mm $\times7$ mm $\times0.508$ mm with a Rogers RT/Duroid 5880 substrate. Effective operation is demonstrated in sub-6 GHz bands (5G at 3.8 GHz, LTE band-46 at 5.4 GHz), complying with safety standards (specific absorption rate and power density) set by the Institute of Electrical and Electronics Engineers and the International Commission on Non-Ionizing Radiation Protection. Efficient performance extends to the 5G mm-wave band at 28 GHz, making it a promising choice for modern smartphone applications.

Abstract Background Fabry disease is a rare inherited disorder resulting from deficient α-galactosidase A enzyme activity. Common disease manifestations are sweating abnormalities, neuropathic pain, gastrointestinal symptoms and fatigue. Challenges are faced by health care professionals in evaluating symptom burden in the current clinical setting, and the demand for alternative methods for monitoring disease-specific symptoms has seen an acceleration in recent years. Smartphone technologies offer the potential for continuity of care and surveillance. As a part of a quality improvement project, a disease specific app was developed in collaboration with a software company (Health Touch Ltd) and made available for patient use in May 2018. The Fabry mobile app records five categories: pain, gastrointestinal symptoms, sweating, activity levels, medications. Fabry disease patients with gastrointestinal and pain symptoms attending the Lysosomal Storage Disorders Unit of the Royal Free London NHS Foundation Trust were reviewed to assess eligibility and invited to download the app for recording their symptoms (activity, sweating, pain and gastrointestinal) and medications. Patient-generated data were transmitted to a secure website for clinicians to review. Results One-hundred and thirty-nine symptomatic Fabry disease patients who had a smartphone (iPhone or android) were invited to download the app. Sixty-seven patients (26 males and 41 females; median age, 49 years [range, 20–81]) downloaded and tracked the Fabry App at least once. The median frequency of use per patient was 6 (range, 1–629). Pain in the hands and abdominal pain were significantly higher (p = 0.009 and p = 0.007, respectively) in patients with classic phenotype compared with patients with non-classic phenotypes. Conclusions We demonstrated the feasibility and acceptability of a smartphone app to facilitate the remote assessment and monitoring of Fabry disease symptom burden on a daily/weekly basis, as an alternative to the current standard of care that requires patients to recall their symptoms during 6 to 12 monthly annual clinic visits. Patients who were more likely to use the app had greater disease burden. This innovation has the potential to assess disease progression, early therapeutic intervention, thereby decreasing the burden of morbidity and mortality among Fabry patients, and to record long-term effects of Fabry-specific therapies.

Abstract Background and Aim Chronic liver disease and cirrhosis is a significant cause of healthcare utilization and patient morbidity and mortality worldwide. Smartphone applications have high uptake in most communities and therefore have great potential to provide remote support solutions to this patient population. The aim of this scoping review was therefore to provide a comprehensive overview using narrative synthesis on the use of smartphone‐application‐based digital interventions in cirrhotic populations. Materials and Methods PRISMA guidelines were followed, with two independent researchers identifying 10 relevant studies. Patients studied were predominantly those with decompensated cirrhosis, and hepatic encephalopathy was the most common complication studied. Results Smartphones were the most common platform used, but training periods, prior to commencement of the study, were rarely offered. Patient engagement rates with the technology were reported only in three studies, but all reported high (>50%) rates of engagement. Only one study examined the clinical effects of their digital intervention, with a 38% reduction in readmission rate reported. Conclusion Overall, the use of smartphone apps in cirrhosis is in an early phase of development and evaluation but preliminary studies suggest significant potential as an adjunct to routine medical care. Further high‐quality studies of well‐designed digital interventions are needed to advance this promising early experience.

Background: Sushruta (600 B.C.) described a condition called “Vidari” linked with progressive narrowing of mouth, depigmentation of the oral mucosa, and pain on taking food, oral submucous fibrosis (OSMF). In 1952, Schwartz called this illness, which affected five Indian women existing in Kenya, “atrophica idiopathica mucosae oris.” Pindborg and Sirsat coined the term “oral submucous fibrosis” in 1966, which is still in use today. With an overall Indian prevalence rate of between 0.2–0.5%, OSMF is primarily found in India and Southeast Asia, according to global estimations. Patients with OSMF need regular follow-ups and to maintain this follow-up it is not always possible for the patient to visit a dental clinic. Hence developing a smartphone-based application for the follow-up of OSMF will be of great value to the patients. The study aims to evaluate the effectiveness of a smartphone application on OSMF self-examination in the follow-up of patients. Methods: There will be three phases of the research. The first phase will be the development of a smartphone-based application for the follow-up of patients with OSMF. The second phase will be distribution and training the patients regarding the usage of the application and the third phase will be evaluating the effectiveness of the smartphone application in maintaining the follow-up of the patients. Expected results: The follow-up of patients with OSMF is expected to be better and feasible using a smartphone application as compared to regular Outpatient Department-based follow-up. Conclusions: Designing a mobile application for the ease of users presents difficulties since it must take accessibility into account, which influences how well the application is received by users. The goal of OSMF examination awareness facilitation and intervention is to raise public knowledge. Educational activities significantly contribute to the advancement of information, convictions, and OSMF screening practice. CTRI registration: CTRI/2023/06/054514 (registration pending)

Background: Fabry disease is a rare inherited disorder resulting from deficient α-galactosidase A enzyme activity. Common disease manifestations are sweating abnormalities, neuropathic pain, gastrointestinal symptoms and fatigue. Challenges are faced by health care professionals in evaluating symptom burden in the current clinical setting, and the demand for alternative methods for monitoring disease-specific symptoms has seen an acceleration in recent years. Smartphone technologies offer the potential for continuity of care and surveillance. As a part of a quality improvement project, a disease specific app was developed in collaboration with a software company (Health Touch Ltd) and made available for patient use in May 2018. The Fabry mobile app records five categories: pain, gastrointestinal symptoms, sweating, activity levels, medications. Fabry disease patients with gastrointestinal and pain symptoms attending the Lysosomal Storage Disorders Unit of the Royal Free London NHS Foundation Trust were reviewed to assess eligibility and invited to download the app for recording their symptoms (activity, sweating, pain and gastrointestinal) and medications. Patient-generated data were transmitted to a secure website for clinicians to review. Results: One-hundred and thirty-nine symptomatic Fabry disease patients who had a smartphone (iPhone or android) were invited to download the app. Sixty-seven patients (26 males and 41 females; median age, 49 years [range, 20–81]) downloaded and tracked the Fabry App at least once. The median frequency of use per patient was 6 (range, 1–629). Pain in the hands and abdominal pain were significantly higher (p = 0.009 and p = 0.007, respectively) in patients with classic phenotype compared with patients with non-classic phenotypes. Conclusions: We demonstrated the feasibility and acceptability of a smartphone app to facilitate the remote assessment and monitoring of Fabry disease symptom burden on a daily/weekly basis, as an alternative to the current standard of care that requires patients to recall their symptoms during 6 to 12 monthly annual clinic visits. Patients who were more likely to use the app had greater disease burden. This innovation has the potential to assess disease progression, early therapeutic intervention, thereby decreasing the burden of morbidity and mortality among Fabry patients, and to record long-term effects of Fabry-specific therapies. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this publication is to present the usage of smartphone application in Smart Cities in environmental monitoring. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: This publication delves into the multifaceted role of smartphone applications within smart cities, with a specific focus on key areas like air quality, noise pollution, water quality, and weather conditions. The integration of these applications not only tackles environmental issues but also empowers citizens to actively participate in the protection of their surroundings. Notably, air quality monitoring emerges as a standout domain, leveraging built-in sensors to measure pollutants in real-time, thereby enabling informed decision-making and contributing to public health awareness. The comprehensive overview presented in this publication underscores the transformative impact of smartphone applications, emphasizing their role in fostering smarter and more sustainable urban environments. The democratization of environmental data through these tools not only raises awareness but also encourages behavioral changes, cultivating a sense of environmental stewardship among citizens. As citizens increasingly engage in assessing air quality, noise pollution, water quality, and weather conditions, the publication highlights the transformative leap that smartphone applications represent in the journey towards smart cities. This evolution not only enhances individual decision-making but also nurtures a collective responsibility for creating urban environments that are both sustainable and resilient. Looking ahead, as technology continues to advance, smartphone applications are poised to play an increasingly pivotal role, promising a future where citizens and smart cities collaborate to ensure the well-being of both urban dwellers and the planet. Originality/value: Detailed analysis of usage smartphone applications in environmental monitoring area. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this publication is to present the usage of smartphone application in Smart Cities in community engagement. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: The integration of smartphone applications in community engagement within smart cities signifies a transformative paradigm shift, offering a myriad of advantages that redefine residents' interactions and contributions to community development. These applications act as dynamic platforms, utilizing technology to amplify communication, collaboration, and participation, fostering a more connected and empowered citizenry. The benefits encompass immediate access to real-time information, heightened civic participation, participatory decision-making, efficient public services, sustainability promotion, community building, emergency response, education, cultural and recreational engagement, and inclusive accessibility. Nevertheless, the implementation of smartphone applications in community engagement encounters challenges, including digital inequality, privacy concerns, technological literacy limitations, language and cultural barriers, security risks, exclusion of vulnerable groups, and issues related to data accuracy and reliability. To ensure inclusivity, effectiveness, and equity, it is imperative to actively address these challenges, emphasizing social equity considerations and balancing technological innovation with the diverse needs of the entire community. Bridging digital divides, providing education and support, addressing privacy issues, and promoting a balanced approach to technology use are vital steps toward creating truly inclusive and effective community engagement strategies in smart cities. Through thoughtful consideration and proactive measures, smart cities can fully harness the potential of smartphone applications to create vibrant, connected, and resilient urban communities. Originality/value: Detailed analysis of usage smartphone applications in the case of community engagement [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this publication is to present the usage of smartphone application in Smart Cities in energy efficiency management. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: The rise of the Internet of Things has made smart devices commonplace in homes and businesses. Smartphone apps play a key role in enabling users to control and monitor these devices, thereby enhancing energy efficiency. Real-time data on energy consumption informs users' decisions, leading to reduced energy waste and costs. These apps not only offer convenience but also support customization and automation for energy-efficient operations. Participation in demand response programs and integration with renewable energy sources further enhance energy efficiency. Smartphone applications also contribute to eco-friendly commuting and optimized waste management, while educating users about their environmental impact and ways to reduce energy consumption sustainably. Despite their advantages, smartphone applications face challenges related to data privacy, adoption, compatibility, user education, reliability, affordability, and access inequalities. Overcoming these challenges is crucial for smart city planners and developers to fully harness the potential of smartphone applications in creating energy-efficient and sustainable smart cities. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this publication is to present the usage of smartphone application in Smart Cities in waste management. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: The integration of smartphone apps in smart city waste management promises enhanced urban sustainability, efficiency, and citizen engagement. These apps, detailed in Tables 1 and 2, offer real-time monitoring, data-driven decision-making, and environmental benefits. Yet, challenges like the digital divide and data privacy, discussed in Table 3, must be overcome. A comprehensive approach, focusing on accessibility, data security, and sustainability, is essential. Smartphone apps are a critical step toward creating cleaner, healthier, and more sustainable smart cities. [ABSTRACT FROM AUTHOR]

Background and Aim: Chronic liver disease and cirrhosis is a significant cause of healthcare utilization and patient morbidity and mortality worldwide. Smartphone applications have high uptake in most communities and therefore have great potential to provide remote support solutions to this patient population. The aim of this scoping review was therefore to provide a comprehensive overview using narrative synthesis on the use of smartphone‐application‐based digital interventions in cirrhotic populations. Materials and Methods: PRISMA guidelines were followed, with two independent researchers identifying 10 relevant studies. Patients studied were predominantly those with decompensated cirrhosis, and hepatic encephalopathy was the most common complication studied. Results: Smartphones were the most common platform used, but training periods, prior to commencement of the study, were rarely offered. Patient engagement rates with the technology were reported only in three studies, but all reported high (>50%) rates of engagement. Only one study examined the clinical effects of their digital intervention, with a 38% reduction in readmission rate reported. Conclusion: Overall, the use of smartphone apps in cirrhosis is in an early phase of development and evaluation but preliminary studies suggest significant potential as an adjunct to routine medical care. Further high‐quality studies of well‐designed digital interventions are needed to advance this promising early experience. [ABSTRACT FROM AUTHOR]

Background:: Human user authentication can be implemented by token-, keyword-, or identity-based mechanisms for digital environment session entry (i.e., smartphones, platforms with log-in). Physiological signals, such as ECG, have shown discriminative properties for user identity recognition. Due to ECG hidden nature, it is resilient to public trait exposition, light/noise saturation, or eavesdropping in contrast to fingerprint, facial, voice, or password approaches. ECG might fill those gaps toward a cooperative authentication environment. Methods:: This paper proposes a Deep Learning identification scenario in which the inclusion of sex recognition directs the input sample toward a sex-specialized identity classification model, simplifying the discrimination space for each model. The architecture proposed could be suitable for large populations. Our scheme worked with an ECG three-axis pseudo-orthogonal configuration in which each axis is transformed into a time-frequency space. Additionally, we combine each lead matrix in an RGB image, joining the contribution of each wavelet waveform. Results:: Our results suggest that it is possible to identify people by using RGB wavelet representations, achieving a classification average of 99.97%. In addition, the inclusion of the sex category for our identification purpose does not significantly affect the classification performance, making it a feasible solution for systems with a larger population. Conclusions:: With the features of our database, we have evidence that it is possible to recognize a person’s identity using an ECG sex recognition module through our proposed architecture.

Topic: Numerous smartphone applications have been devised for diagnosis, treatment, and symptom management in ophthalmology. Despite the importance of systematic evaluation of the purpose, target disease, effectiveness, and utility of smartphone applications to their effective utilization, few studies have formally evaluated their validity, reliability, and clinical utility. Clinical Relevance: This report identifies smartphone applications with potential for clinical implementation in ophthalmology and summarizes the evidence on their practical utility. Methods: We searched PubMed and EMBASE on July 28, 2022, for articles reporting original data on the effectiveness of treatment, disease detection, diagnostic accuracy, disease monitoring, and usability of smartphone applications in ophthalmology published between January 1, 1987, and July 25, 2022. Their quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Results: The initial search yielded 510 articles. After removing 115 duplicates and 285 articles based on inclusion and exclusion criteria, the full texts of the remaining 110 articles were reviewed. Furthermore, 71 articles were included in the final qualitative synthesis. All studies were determined to be of high (87.3%) or moderate (12.7%) quality. In terms of respective application of interest, 24 (33.8%) studies assessed diagnostic accuracy, 17 (23.9%) assessed disease detection, and 3 (4.2%) assessed intervention efficacy. A total of 48 smartphone applications were identified, of which 27 (56.3%) were publicly available. Seventeen (35.4%) applications included functions for ophthalmic examinations, 13 (27.1%) included functions aimed at disease detection, 10 (20.8%) included functions to support medical personnel, five (10.4%) included functions related to disease education, and three (6.3%) included functions to promote treatment adherence for patients. The largest number of applications targeted amblyopia (18.8%), followed by retinal disease (10.4%). Two (4.2%) smartphone applications reported significant efficacy in treating diseases. Conclusion: In this systematic review, a comprehensive appraisal is presented on studies related to diagnostic accuracy, disease detectability, and efficacy of smartphone applications in ophthalmology. Forty-eight applications with potential clinical utility are identified. Appropriate smartphone applications are expected to enable early detection of undiagnosed diseases via telemedicine and prevent visual dysfunction via remote monitoring of chronic diseases. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references.

A cataract is one of the most significant eye problems worldwide that does not immediately impair vision and progressively worsens over time. Automatic cataract prediction based on various imaging technologies has been addressed recently, such as smartphone apps used for remote health monitoring and eye treatment. In recent years, advances in diagnosis, prediction, and clinical decision support using Artificial Intelligence (AI) in medicine and ophthalmology have been exponential. Due to privacy concerns, a lack of datamakes applying artificial intelligence models in themedical field challenging. To address this issue, a federated learning framework named CD-FL based on aVGG16 deep neural networkmodel is proposed in this research. The study collects data from the Ocular Disease Intelligent Recognition (ODIR) database containing 5,000 patient records. The significant features are extracted and normalized using the min-max normalization technique. In the federated learning-based technique, the VGG16 model is trained on the dataset individually after receiving model updates from two clients. Before transferring the attributes to the global model, the suggested method trains the local model. The global model subsequently improves the technique after integrating the new parameters. Every client analyses the results in three rounds to decrease the over-fitting problem. The experimental result shows the effectiveness of the federated learning-based technique on a Deep Neural Network (DNN), reaching a 95.28% accuracy while also providing privacy to the patient's data. The experiment demonstrated that the suggested federated learning model outperforms other traditional methods, achieving client 1 accuracy of 95.0% and client 2 accuracy of 96.0%. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this publication is to present the usage of smartphone application in Smart Cities in public safety and emergency services. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: The integration of smartphone applications into smart city development for public safety and emergency services is a pivotal step toward creating safer, more efficient, and resilient urban environments. These apps empower citizens and authorities to collaborate effectively, enhancing response times and resource allocation during emergencies. Smartphone applications also provide timely alerts, navigation tools, and educational resources for disaster preparedness. However, challenges like limited access, privacy concerns, and digital literacy gaps must be addressed to fully harness their potential. Embracing these challenges through technology enhancements and user education can lead to safer and smarter urban environments. Originality/value: Detailed analysis of all subjects related to the problems connected with the usage of smartphone applications in public safety and emergency services. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this publication is to present the usage of smartphone application in Smart Cities in urban mobility and traffic management. Design/methodology/approach: Critical literature analysis. Analysis of international literature from main databases and polish literature and legal acts connecting with researched topic. Findings: Smartphone applications have undeniably transformed urban mobility and traffic management in smart cities. Their real-time data capabilities, optimization features, and userfriendly interfaces have created more efficient, sustainable, and enjoyable transportation systems. However, it is essential for smart cities to tackle the associated challenges effectively, ensuring that these applications contribute to equitable, safe, and efficient transportation systems within the urban landscape. The future of urban mobility is digital, and it's driven by the convenience and connectivity offered by our smartphones. Originality/value: Detailed analysis of all subjects related to the problems connected with the usage of smartphone applications in urban mobility and traffic management in smart cities. [ABSTRACT FROM AUTHOR]

ObjectiveTo elicit feedback on the acceptability, usability, and dissemination options for the bMOREsafe smartphone application (app). Participants: Forty-nine students and six service-providers provided feedback on the bMOREsafe app between April 2015 and March 2016. Methods: Students responded to an anonymous online survey and providers participated in semi-structured interviews. Descriptive and thematic analyses were completed. Results: Students rated the app as useful, however less applicable to themselves and their peers. Students stated they would be most receptive to recommendations about the app from peers and social media. Qualitative data from service providers fell into three main categories: trauma-informed aspects; inclusivity vs. specificity; and within an app, language matters. Conclusions: Smartphone technology can provide confidential information and resources to help students make decisions related to sexual assault or intimate partner violence care. While students and providers identified apps as a useful strategy for sharing this information, dissemination challenges remain.

IntroductionPlant identification applications for use on smartphones have been increasing in availability, accuracy, and utilization. We aimed to perform an introductory study to determine if a plant identification application (ID app) used on a smartphone could identify toxic plants, and to compare apps to determine which is most reliable.MethodsWe compared three popular iPhone plant ID apps, PictureThis (PT), PlantSnap (PS), and Pl@ntNet (PN), used to identify 17 commonly encountered toxic plants. Apps were used to photograph the entire plant, leaves, and flowers of ≥ 10 different plants for each species. Two toxicologists performed plant identification with confirmation of identification performed by a botanist, and inter-researcher agreement was confirmed. For each plant species, scores for accuracy of app identification of leaves, flowers, and whole plant were combined to create an overall composite score used to compare accuracy of each app (95% C.I.).ResultsPictureThis had the best performance with 10/17 (59% [36 to 78]) plant species identified 100% correctly, as opposed to 8/17 (47% [26 to 69]) for Pl@ntNet and 1/17 for PlantSnap (5.8% [1.1 to 27]).ConclusionA plant identification app may be a useful tool to assist healthcare providers and the public in identifying toxic plants.

The writer has a poor sense of orientation and loses her way when she walks in cities. When this happens in Antwerp, Belgium, GPS maps and a music streaming application on her smartphone trigger the experience that she unfolds in this essay. Her aim is to explore an aspect of the temporal dynamics of contemporary life and, based on the element of loss, to demonstrate how machine, digital temporality and human, existential temporality may interact. Thanks to Kenneth Goldsmith's notion of displacement, the work of writers and artists related to Antwerp, namely Hugo Claus, Connie Palmen and Jan Fabre, references to ethnology and performance studies, and the writer’s father who was gardening through bud grafting, the experience of losing one’s way in a city with a smartphone in the hand, is restaged in writing, while loss in space encounters memory through oblivion and initiates reflection on an existential condition of loss.

Exposure to potentially toxic plants is a global problem, resulting in thousands of calls to poison centers and emergency department visits annually and occasional deaths. Persons with limited botanical knowledge may be tempted to rely on smartphone applications to determine if plants are safe to forage. This study evaluated the reliability of several popular smartphone applications to identify foraged foods and distinguish them from potentially toxic plants in the Midwestern United States. Sixteen plant species were selected based on local availability, attractiveness as foraged food, and potential for misidentification. Of the 16 species, five are edible, three are potentially toxic if improperly harvested or prepared, and eight are considered to be toxic. Plant specimens were identified by graduate-level botanists and photographed during multiple stages of their growth cycles. LeafSnap, PictureThis, Pl@ntNet and PlantSnap were used to identify the plants. Overall accuracy of the applications in identifying plant genus was 76% (95% confidence interval: 73–79, range 96% for PictureThis to 53% for PlantSnap). Accuracy for identification of plant species was 58% (95% confidence interval 55–62%, range 94% for PictureThis to 34% for PlantSnap). Five of eleven potentially toxic species were identified as an edible species by at least one application. Accuracy of the smartphone applications varies, with PictureThis outperforming other apps. At this time, apps cannot be used to safely identify edible plants. Foragers must have adequate botanical knowledge to ensure safe harvesting of wild plants. [ABSTRACT FROM AUTHOR]

Simple Summary: Non-melanoma skin cancer is one of the most common cancer diagnoses in the world, and cases are rising globally. Consequently, novel technology to aid in screening is of interest. Deep learning is one type of artificial intelligence that has shown promise in image analysis and is an attractive tool for application in non-melanoma skin cancer diagnosis. Here, we review the evidence for deep learning in non-melanoma skin cancer screening and diagnosis, the available technologies and remote applications, and attitudes and ethical considerations regarding such technologies. Skin cancer is the most common cancer diagnosis in the United States, with approximately one in five Americans expected to be diagnosed within their lifetime. Non-melanoma skin cancer is the most prevalent type of skin cancer, and as cases rise globally, physicians need reliable tools for early detection. Artificial intelligence has gained substantial interest as a decision support tool in medicine, particularly in image analysis, where deep learning has proven to be an effective tool. Because specialties such as dermatology rely primarily on visual diagnoses, deep learning could have many diagnostic applications, including the diagnosis of skin cancer. Furthermore, with the advancement of mobile smartphones and their increasingly powerful cameras, deep learning technology could also be utilized in remote skin cancer screening applications. Ultimately, the available data for the detection and diagnosis of skin cancer using deep learning technology are promising, revealing sensitivity and specificity that are not inferior to those of trained dermatologists. Work is still needed to increase the clinical use of AI-based tools, but based on the current data and the attitudes of patients and physicians, deep learning technology could be used effectively as a clinical decision-making tool in collaboration with physicians to improve diagnostic efficiency and accuracy. [ABSTRACT FROM AUTHOR]

We use data on human mobility obtained from mobile applications to explore the activity patterns in the neighbourhoods of Greater London as they emerged from the first wave of COVID-19 lockdown restrictions during summer 2020 and analyse how the lockdown guidelines have exposed the socio-spatial fragmentation between urban communities. The location data are spatially aggregated to 1 km2 grids and cross-checked against publicly available mobility metrics (e.g. Google COVID-19 Community Report, Apple Mobility Trends Report). They are then linked to geodemographic classifications to compare the average decline of activities in the areas with different sociodemographic characteristics. We found that the activities in the deprived areas dominated by minority groups declined less compared to the Greater London average, leaving those communities more exposed to the virus. Meanwhile, the activity levels declined more in affluent areas dominated by white-collar jobs. Furthermore, due to the closure of non-essential stores, activities declined more in premium shopping destinations and less in suburban high streets. [ABSTRACT FROM AUTHOR]

Human sex recognition with electrocardiogram signals is an emerging area in machine learning, mostly oriented toward neural network approaches. It might be the beginning of a field of heart behavior analysis focused on sex. However, a person's heartbeat changes during daily activities, which could compromise the classification. In this paper, with the intention of capturing heartbeat dynamics, we divided the heart rate into different intervals, creating a specialized identification model for each interval. The sexual differentiation for each model was performed with a deep convolutional neural network from images that represented the RGB wavelet transformation of ECG pseudo-orthogonal X, Y, and Z signals, using sufficient samples to train the network. Our database included 202 people, with a female-to-male population ratio of 49.5–50.5% and an observation period of 24 h per person. As our main goal, we looked for periods of time during which the classification rate of sex recognition was higher and the process was faster; in fact, we identified intervals in which only one heartbeat was required. We found that for each heart rate interval, the best accuracy score varied depending on the number of heartbeats collected. Furthermore, our findings indicated that as the heart rate increased, fewer heartbeats were needed for analysis. On average, our proposed model reached an accuracy of 94.82% ± 1.96%. The findings of this investigation provide a heartbeat acquisition procedure for ECG sex recognition systems. In addition, our results encourage future research to include sex as a soft biometric characteristic in person identification scenarios and for cardiology studies, in which the detection of specific male or female anomalies could help autonomous learning machines move toward specialized health applications. [ABSTRACT FROM AUTHOR]